library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.3 ✓ purrr 0.3.4
## ✓ tibble 3.1.0 ✓ dplyr 1.0.5
## ✓ tidyr 1.1.3 ✓ stringr 1.4.0
## ✓ readr 1.4.0 ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(lubridate)
##
## Attaching package: 'lubridate'
## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union
library(gganimate)
library(transformr)
library(magick)
## Linking to ImageMagick 6.9.11.57
## Enabled features: cairo, fontconfig, freetype, heic, lcms, pango, raw, rsvg, webp
## Disabled features: fftw, ghostscript, x11
time_series_confirmed <- read_csv(url("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv")) %>%
rename(Province_State = "Province/State", Country_Region = "Country/Region")
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double(),
## `Province/State` = col_character(),
## `Country/Region` = col_character()
## )
## ℹ Use `spec()` for the full column specifications.
download.file(url="https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv",
destfile = "data/time_series_covid19_confirmed_global.csv")
time_series_confirmed <- read_csv("data/time_series_covid19_confirmed_global.csv")%>%
rename(Province_State = "Province/State", Country_Region = "Country/Region")
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double(),
## `Province/State` = col_character(),
## `Country/Region` = col_character()
## )
## ℹ Use `spec()` for the full column specifications.
head(time_series_confirmed)
## # A tibble: 6 x 417
## Province_State Country_Region Lat Long `1/22/20` `1/23/20` `1/24/20`
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 <NA> Afghanistan 33.9 67.7 0 0 0
## 2 <NA> Albania 41.2 20.2 0 0 0
## 3 <NA> Algeria 28.0 1.66 0 0 0
## 4 <NA> Andorra 42.5 1.52 0 0 0
## 5 <NA> Angola -11.2 17.9 0 0 0
## 6 <NA> Antigua and Barbuda 17.1 -61.8 0 0 0
## # … with 410 more variables: 1/25/20 <dbl>, 1/26/20 <dbl>, 1/27/20 <dbl>,
## # 1/28/20 <dbl>, 1/29/20 <dbl>, 1/30/20 <dbl>, 1/31/20 <dbl>, 2/1/20 <dbl>,
## # 2/2/20 <dbl>, 2/3/20 <dbl>, 2/4/20 <dbl>, 2/5/20 <dbl>, 2/6/20 <dbl>,
## # 2/7/20 <dbl>, 2/8/20 <dbl>, 2/9/20 <dbl>, 2/10/20 <dbl>, 2/11/20 <dbl>,
## # 2/12/20 <dbl>, 2/13/20 <dbl>, 2/14/20 <dbl>, 2/15/20 <dbl>, 2/16/20 <dbl>,
## # 2/17/20 <dbl>, 2/18/20 <dbl>, 2/19/20 <dbl>, 2/20/20 <dbl>, 2/21/20 <dbl>,
## # 2/22/20 <dbl>, 2/23/20 <dbl>, 2/24/20 <dbl>, 2/25/20 <dbl>, 2/26/20 <dbl>,
## # 2/27/20 <dbl>, 2/28/20 <dbl>, 2/29/20 <dbl>, 3/1/20 <dbl>, 3/2/20 <dbl>,
## # 3/3/20 <dbl>, 3/4/20 <dbl>, 3/5/20 <dbl>, 3/6/20 <dbl>, 3/7/20 <dbl>,
## # 3/8/20 <dbl>, 3/9/20 <dbl>, 3/10/20 <dbl>, 3/11/20 <dbl>, 3/12/20 <dbl>,
## # 3/13/20 <dbl>, 3/14/20 <dbl>, 3/15/20 <dbl>, 3/16/20 <dbl>, 3/17/20 <dbl>,
## # 3/18/20 <dbl>, 3/19/20 <dbl>, 3/20/20 <dbl>, 3/21/20 <dbl>, 3/22/20 <dbl>,
## # 3/23/20 <dbl>, 3/24/20 <dbl>, 3/25/20 <dbl>, 3/26/20 <dbl>, 3/27/20 <dbl>,
## # 3/28/20 <dbl>, 3/29/20 <dbl>, 3/30/20 <dbl>, 3/31/20 <dbl>, 4/1/20 <dbl>,
## # 4/2/20 <dbl>, 4/3/20 <dbl>, 4/4/20 <dbl>, 4/5/20 <dbl>, 4/6/20 <dbl>,
## # 4/7/20 <dbl>, 4/8/20 <dbl>, 4/9/20 <dbl>, 4/10/20 <dbl>, 4/11/20 <dbl>,
## # 4/12/20 <dbl>, 4/13/20 <dbl>, 4/14/20 <dbl>, 4/15/20 <dbl>, 4/16/20 <dbl>,
## # 4/17/20 <dbl>, 4/18/20 <dbl>, 4/19/20 <dbl>, 4/20/20 <dbl>, 4/21/20 <dbl>,
## # 4/22/20 <dbl>, 4/23/20 <dbl>, 4/24/20 <dbl>, 4/25/20 <dbl>, 4/26/20 <dbl>,
## # 4/27/20 <dbl>, 4/28/20 <dbl>, 4/29/20 <dbl>, 4/30/20 <dbl>, 5/1/20 <dbl>,
## # 5/2/20 <dbl>, 5/3/20 <dbl>, …
time_series_confirmed_long <- time_series_confirmed %>%
pivot_longer(-c(Province_State, Country_Region, Lat, Long),
names_to = "Date", values_to = "Confirmed")
time_series_confirmed_long$Date <- mdy(time_series_confirmed_long$Date)
head(time_series_confirmed_long)
## # A tibble: 6 x 6
## Province_State Country_Region Lat Long Date Confirmed
## <chr> <chr> <dbl> <dbl> <date> <dbl>
## 1 <NA> Afghanistan 33.9 67.7 2020-01-22 0
## 2 <NA> Afghanistan 33.9 67.7 2020-01-23 0
## 3 <NA> Afghanistan 33.9 67.7 2020-01-24 0
## 4 <NA> Afghanistan 33.9 67.7 2020-01-25 0
## 5 <NA> Afghanistan 33.9 67.7 2020-01-26 0
## 6 <NA> Afghanistan 33.9 67.7 2020-01-27 0
time_series_confirmed_long%>%
group_by(Country_Region, Date) %>%
summarise(Confirmed = sum(Confirmed)) %>%
filter (Country_Region == "US") %>%
ggplot(aes(x = Date, y = Confirmed)) +
geom_point() +
geom_line() +
ggtitle("US COVID-19 Confirmed Cases")
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
time_series_confirmed_long %>%
group_by(Country_Region, Date) %>%
summarise(Confirmed = sum(Confirmed)) %>%
filter (Country_Region %in% c("China","France","Italy",
"Korea, South", "US")) %>%
ggplot(aes(x = Date, y = Confirmed, color = Country_Region)) +
geom_point() +
geom_line() +
ggtitle("COVID-19 Confirmed Cases")
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
time_series_confirmed_long_daily <-time_series_confirmed_long %>%
group_by(Country_Region, Date) %>%
summarise(Confirmed = sum(Confirmed)) %>%
mutate(Daily = Confirmed - lag(Confirmed, default = first(Confirmed )))
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
time_series_confirmed_long_daily %>%
filter (Country_Region == "US") %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
geom_point() +
ggtitle("COVID-19 Confirmed Cases")
time_series_confirmed_long_daily %>%
filter (Country_Region == "US") %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
geom_line() +
ggtitle("COVID-19 Confirmed Cases")
time_series_confirmed_long_daily %>%
filter (Country_Region == "US") %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
geom_smooth() +
ggtitle("COVID-19 Confirmed Cases")
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
time_series_confirmed_long_daily %>%
filter (Country_Region == "US") %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
geom_smooth(method = "gam", se = FALSE) +
ggtitle("COVID-19 Confirmed Cases")
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'
# set eval false to save time on knits
theme_set(theme_bw())
daily_counts <- time_series_confirmed_long_daily %>%
filter (Country_Region == "US")
p <- ggplot(daily_counts, aes(x = Date, y = Daily, color = Country_Region)) +
geom_point() +
ggtitle("Confirmed COVID-19 Cases") +
geom_point(aes(group = seq_along(Date))) +
transition_reveal(Date)
# Some people using a local installation of RStudio may needed to use this line instead
animate(p, renderer = magick_renderer(), end_pause = 15)
anim_save("daily_counts_US.gif", p)
#1
time_series_confirmed_long %>%
group_by(Country_Region, Date) %>%
summarise(Confirmed = sum(Confirmed)) %>%
filter (Country_Region %in% c("Brazil","India","Germany",
"Russia", "US")) %>%
ggplot(aes(x = Date, y = Confirmed, color = Country_Region)) +
facet_wrap(facets = vars(Country_Region), scales="free_y") +
geom_point() +
geom_line() +
ggtitle("COVID-19 Confirmed Cases")
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
#2
time_series_confirmed_long %>%
group_by(Country_Region, Date) %>%
summarise(Confirmed = sum(Confirmed)) %>%
filter (Country_Region %in% c("Brazil","India","Germany",
"Russia", "US")) %>%
ggplot(aes(x = Date, y = Confirmed, color = Country_Region)) +
geom_point() +
geom_line() +
ggtitle("COVID-19 Confirmed Cases")
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
#3
download.file(url="https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv",
destfile = "data/time_series_covid19_deaths_global.csv")
time_series_deaths <- read_csv("data/time_series_covid19_deaths_global.csv")%>%
rename(Province_State = "Province/State", Country_Region = "Country/Region")
##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## .default = col_double(),
## `Province/State` = col_character(),
## `Country/Region` = col_character()
## )
## ℹ Use `spec()` for the full column specifications.
time_series_deaths_long <- time_series_deaths %>%
pivot_longer(-c(Province_State, Country_Region, Lat, Long),
names_to = "Date", values_to = "Deaths")
time_series_deaths_long$Date <- mdy(time_series_deaths_long$Date)
time_series_deaths_long %>%
group_by(Country_Region, Date) %>%
summarise(Deaths = sum(Deaths)) %>%
filter (Country_Region %in% c("Mexico","Canada", "US")) %>%
ggplot(aes(x = Date, y = Deaths, color = Country_Region)) +
geom_line() +
geom_point() +
ggtitle("COVID-19 Deaths")
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
#head(time_series_deaths_long)
#4
time_series_deaths_long_daily <- time_series_deaths_long %>%
group_by(Country_Region, Date) %>%
summarise(Deaths = sum(Deaths)) %>%
mutate(Daily = Deaths - lag(Deaths, default = first(Deaths)))
## `summarise()` has grouped output by 'Country_Region'. You can override using the `.groups` argument.
ex4_graph <- time_series_deaths_long_daily %>%
filter (Country_Region %in% c("Mexico","Canada", "US")) %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
ggtitle("COVID-19 Confirmed Cases") +
geom_smooth(method = "gam", se = FALSE)
ex4_graph
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'
#5
ex5_graph <- time_series_deaths_long_daily %>%
filter (Country_Region %in% c("Brazil","India","Germany",
"Russia", "US")) %>%
ggplot(aes(x = Date, y = Daily, color = Country_Region)) +
geom_smooth(method = "gam", se = FALSE)
ggtitle("COVID-19 Confirmed Cases")
## $title
## [1] "COVID-19 Confirmed Cases"
##
## attr(,"class")
## [1] "labels"
ex5_graph
## `geom_smooth()` using formula 'y ~ s(x, bs = "cs")'
#6
daily_counts <- time_series_deaths_long_daily %>%
filter (Country_Region %in% c("Brazil","India","Germany",
"Russia", "US"))
ex6_graph <- ggplot(daily_counts, aes(x = Date, y = Daily, color = Country_Region)) +
geom_line() +
ggtitle("Deaths by COVID-19") +
geom_line(aes(group = seq_along(Date))) +
transition_reveal(Date)
ex6_graph
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?
## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?